Barriers to Change: Climate Change Scepticism and Uncertainty in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In light of increasing green house gas emissions and severity of climate change impacts, elucidating the psychological barriers that limit climate change mitigation behaviour, especially in individuals from industrialised countries with poor mitigation performance, is important. This study sought to establish the extent of climate change scepticism and uncertainty in a representative sample of Anglophone Canadians, and determine the association with values, knowledge and socio-demographic factors. 229 participants responded to a mail invitation to take part in the online survey. Scepticism and uncertainty toward climate change were assessed using an attitudinal index that yielded a composite scepticism score. Environmental values were assessed using a modified version of the New Environmental Paradigm scale (NEP), and political association, climate change knowledge and several demographic variables were determined using established metrics. A full factor multiple regression analysis showed region, NEP score and Conservative Party of Canada association as the significant predictors of scepticism. Further regression modelling showed that values and politics explained 31% of the variation in scepticism scores, socio-demographic variables 6%, and education and knowledge 3%. These findings highlight the dominant role of environmental values and political orientation, and are discussed in the context of the theory of socially-organised denial of climate change and the information-deficit model of climate inaction.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it